Metastatic breast cancer remains challenging to treat and the 5-year survival rate for patients diagnosed with distant metastasis is below 30%. Targeting later stages of breast cancer (BC) metastasis present important opportunities for therapeutic interventions that has the potential to improve patient-outcomes. However, the molecular mechanisms by which tumor cells extravasate out of endothelial vessels and interact with surrounding tissue of the secondary metastatic site are still unclear. Furthermore, how interactions between tumor and stromal cells in the metastatic microenvironment contribute to differential therapeutic response remain unestablished. Current in vivo approaches from studying BC metastasis are costly, has lengthy read-out time to affect clinical decisions, and is inherently low-throughput. Moreover, the lack of availability of in vitro models that effectively characterize the host-specific multi-cellular interactions and signaling events observed in vivo makes this technically challenging to investigate. Thus, there is a critical need for improved modeling approaches that recapitulates the microenvironmental complexities of normal and diseased tissue and that can accurately predict response to novel treatment options. The project goal is to develop innovative organotypic modelling technologies to identify key tumor-stroma targets influencing BC cell extravasation and growth in the lung. The proposed work will test the hypothesis that tumor-stroma interactions can be targeted to inhibit BC cell extravasation and growth and that by means of organotypic modeling approaches unique sets of interactions can be identified and targeted using a novel combination of therapeutic drugs. The study will explore the following two aims. Aim1 Identify cancer-induced response of the lung microenvironment influencing cancer extravasation and growth behavior. Interactions between BC cells and multiple components of the lung stroma including macrophages, fibroblasts, epithelial cells and relevant extracellular matrices will be investigated. Cell responses including BC extravasation rates, vascular permeability, protein and mRNA expression, cellular metabolism and cytokine secretion will be evaluated. Aim2 Measure cancer and stromal cell response to novel drug combinations targeting multiple interactions within the lung microenvironment to inhibit extravasation and growth of tumor cells. Changes in cellular metabolism will be measured to quantify temporal dynamics of drug response and guide downstream collection of biological responses defined in Aim1. The proposed work will help lay the foundation for future clinical studies using patient-specific models to develop personalized therapy and assess their predictive capability. The overall goal of this proposal is in alignment with the mission of NIH to develop new enabling technologies to characterize pathogenesis of diseases and test new therapies. Training and research goals will use available resources at University of Wisconsin-Madison and resources provided by my mentoring committee, Dr. David Beebe and Dr. Melissa Skala, at Wisconsin Institute for Medical Research and Wisconsin Institute for Discovery.